PARAMETER ESTIMATION FOR WEIBULL DISTRIBUTION WITH RIGHT CENSORED DATA USING EM ALGORITHM

被引:25
|
作者
Ferreira, Luis Andrade [1 ]
Silva, Jose Luis [2 ]
机构
[1] FEUP, Dept Mech Engn, Rua Dr Roberto Frias, P-4200465 Oporto, Portugal
[2] ESTV, Dept Mech Engn & Ind Management, Campus Politecn, P-3504510 Viseu, Portugal
关键词
EM algorithm; parameter estimation; maximum likelihood estimates; reliability; LIKELIHOOD;
D O I
10.17531/ein.2017.2.20
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The maximum-likelihood estimation (MLE) is a method of estimating the parameters of a statistical model for given data. This method allows us to estimate the unknown parameters of a statistical model. These parameters are obtained by maximizing the likelihood function of the model in question. In many practical situations the likelihood function is associated with complex models and the likelihood equation has no explicit analytical solution, it is only possible to have its resolution through numerical methods. The estimation of the parameters of the Weibull distribution by maximum-likelihood method based on information from a historical record with right censored data shows this difficulty. The solution presented in this article entails using the ExpectationMaximization (EM) algorithm. Actual data from the historical record of 5 centrifugal pumps failures of a petrochemical company were analyzed for application of the methodology.
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页码:310 / 315
页数:6
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